关键词: 柔性臂空间机器人, 奇异摄动理论, 径向基函数, 神经网络, 分级模糊控制算法

Abstract: For the general requirement of space robot to have advantages such as long arms and huge load for space on orbit operation, the flexible problem of mechanical arm should be considered for analyzing space robot's dynamics and control. The coordinated motion control and vibration suppression problems of flexible arm space robot with unknown parameters were discussed. With the law of momentum conservation and assumed mode method, the Lagrange principle was utilized to model the dynamic function of flexible arm space robot. On these bases, mathematical models which were suit for control system design were established by using double time scale decomposition of singular perturbation theory. Aiming at the slow subsystem, Radial Basis Function (RBF) neural network control algorithm with uncertain parameters was designed to dominate the trajectory tracking of coordinated motion. The research purpose of neural network control algorithm was to improve the control accuracy of whole system based on good on line self learning of neural network. For fast subsystem, hierarchical fuzzy control algorithm was used to control the vibration of flexible link. The research purpose of hierarchical fuzzy control algorithm was to reduce the size of fuzzy rule base, and raises the calculation efficiency of fuzzy controller effectively. Computer simulation results illustrated the effectiveness and feasibility of proposed algorithms.

Key words: flexible arm space robot, singular perturbation theory, radial basis function, neural network, hierarchical fuzzy control algorithm